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<h2 class="title">
<a id="getting-started-aggregations"></a>Analyze results with aggregations<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/getting-started.asciidoc">edit</a>
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<p>Elasticsearch aggregations enable you to get meta-information about your search results
and answer questions like, "How many account holders are in Texas?" or
"What’s the average balance of accounts in Tennessee?" You can search
documents, filter hits, and use aggregations to analyze the results all in one
request.</p>
<p>For example, the following request uses a <code class="literal">terms</code> aggregation to group
all of the accounts in the <code class="literal">bank</code> index by state, and returns the ten states
with the most accounts in descending order:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">GET /bank/_search
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state.keyword"
      }
    }
  }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/10.console"></div>
<p>The <code class="literal">buckets</code> in the response are the values of the <code class="literal">state</code> field. The
<code class="literal">doc_count</code> shows the number of accounts in each state. For example, you
can see that there are 27 accounts in <code class="literal">ID</code> (Idaho). Because the request
set <code class="literal">size=0</code>, the response only contains the aggregation results.</p>
<div class="pre_wrapper lang-console-result">
<pre class="programlisting prettyprint lang-console-result">{
  "took": 29,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped" : 0,
    "failed": 0
  },
  "hits" : {
     "total" : {
        "value": 1000,
        "relation": "eq"
     },
    "max_score" : null,
    "hits" : [ ]
  },
  "aggregations" : {
    "group_by_state" : {
      "doc_count_error_upper_bound": 20,
      "sum_other_doc_count": 770,
      "buckets" : [ {
        "key" : "ID",
        "doc_count" : 27
      }, {
        "key" : "TX",
        "doc_count" : 27
      }, {
        "key" : "AL",
        "doc_count" : 25
      }, {
        "key" : "MD",
        "doc_count" : 25
      }, {
        "key" : "TN",
        "doc_count" : 23
      }, {
        "key" : "MA",
        "doc_count" : 21
      }, {
        "key" : "NC",
        "doc_count" : 21
      }, {
        "key" : "ND",
        "doc_count" : 21
      }, {
        "key" : "ME",
        "doc_count" : 20
      }, {
        "key" : "MO",
        "doc_count" : 20
      } ]
    }
  }
}</pre>
</div>
<p>You can combine aggregations to build more complex summaries of your data. For
example, the following request nests an <code class="literal">avg</code> aggregation within the previous
<code class="literal">group_by_state</code> aggregation to calculate the average account balances for
each state.</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">GET /bank/_search
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state.keyword"
      },
      "aggs": {
        "average_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/11.console"></div>
<p>Instead of sorting the results by count, you could sort using the result of
the nested aggregation by specifying the order within the <code class="literal">terms</code> aggregation:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">GET /bank/_search
{
  "size": 0,
  "aggs": {
    "group_by_state": {
      "terms": {
        "field": "state.keyword",
        "order": {
          "average_balance": "desc"
        }
      },
      "aggs": {
        "average_balance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/12.console"></div>
<p>In addition to basic bucketing and metrics aggregations like these, Elasticsearch
provides specialized aggregations for operating on multiple fields and
analyzing particular types of data such as dates, IP addresses, and geo
data. You can also feed the results of individual aggregations into pipeline
aggregations for further analysis.</p>
<p>The core analysis capabilities provided by aggregations enable advanced
features such as using machine learning to detect anomalies.</p>
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